CN117538689A - Circuit fault detection method, system, device and medium based on Internet of things - Google Patents

Circuit fault detection method, system, device and medium based on Internet of things Download PDF

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Publication number
CN117538689A
CN117538689A CN202410032014.5A CN202410032014A CN117538689A CN 117538689 A CN117538689 A CN 117538689A CN 202410032014 A CN202410032014 A CN 202410032014A CN 117538689 A CN117538689 A CN 117538689A
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Prior art keywords
module
current
calculation
transmission line
phase
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Inventor
朱绍伟
吴会娟
郝敬密
公伟涛
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Gaotang County Hengcheng Construction Engineering Co ltd
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Gaotang County Hengcheng Construction Engineering Co ltd
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Priority to CN202410032014.5A priority Critical patent/CN117538689A/en
Publication of CN117538689A publication Critical patent/CN117538689A/en
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    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01R—MEASURING ELECTRIC VARIABLES; MEASURING MAGNETIC VARIABLES
    • G01R31/00—Arrangements for testing electric properties; Arrangements for locating electric faults; Arrangements for electrical testing characterised by what is being tested not provided for elsewhere
    • G01R31/08—Locating faults in cables, transmission lines, or networks
    • G01R31/081—Locating faults in cables, transmission lines, or networks according to type of conductors
    • G01R31/085—Locating faults in cables, transmission lines, or networks according to type of conductors in power transmission or distribution lines, e.g. overhead
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01R—MEASURING ELECTRIC VARIABLES; MEASURING MAGNETIC VARIABLES
    • G01R25/00—Arrangements for measuring phase angle between a voltage and a current or between voltages or currents
    • G01R25/005—Circuits for comparing several input signals and for indicating the result of this comparison, e.g. equal, different, greater, smaller, or for passing one of the input signals as output signal
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01R—MEASURING ELECTRIC VARIABLES; MEASURING MAGNETIC VARIABLES
    • G01R31/00—Arrangements for testing electric properties; Arrangements for locating electric faults; Arrangements for electrical testing characterised by what is being tested not provided for elsewhere
    • G01R31/08—Locating faults in cables, transmission lines, or networks
    • G01R31/088—Aspects of digital computing

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  • Physics & Mathematics (AREA)
  • General Physics & Mathematics (AREA)
  • Engineering & Computer Science (AREA)
  • Mathematical Physics (AREA)
  • Theoretical Computer Science (AREA)
  • Locating Faults (AREA)

Abstract

The invention relates to a circuit fault detection method, a system, a device and a medium based on the Internet of things, and relates to the technical field of circuit detection, wherein the circuit fault detection method comprises the steps of monitoring, information acquisition, information uploading, establishing a storage database, periodic component calculation, non-periodic component calculation, actual phase calculation, phase difference value calculation, phase fluctuation judgment, fault position determination, output and the like; the circuit fault detection system comprises a current sensor, an acquisition module, an uploading module, a storage module, a calculation module I, a calculation module II, a calculation module III, a calculation module IV, a judgment module I, a positioning module, a calculation module V, a calculation module VI, a judgment module II and an output module. The invention can monitor the circuit faults at any time, improves the detection precision of the circuit faults and realizes the on-line detection of the circuit faults.

Description

Circuit fault detection method, system, device and medium based on Internet of things
Technical Field
The invention relates to the technical field of circuit detection, in particular to a circuit fault detection method, system, device and medium based on the Internet of things.
Background
The distribution network refers to a power network that receives electric energy from a power transmission network or a regional power plant, and distributes the electric energy locally or step by step according to voltage through a distribution facility. The system consists of overhead lines, cables, towers, distribution transformers, isolating switches, reactive compensators, a plurality of auxiliary facilities and the like, and plays a role in distributing electric energy in a power network.
Currently, when detecting faults of a power transmission line, workers usually detect each section of the power transmission line by an elimination method, and when detecting that a certain section of the power transmission line has faults, the power transmission line is maintained in time.
However, because the distance of the power transmission line is longer, when the power transmission line fails, the failure of the line and the position of the line failure cannot be found in time, and how to realize on-line monitoring of the circuit failure and improve the detection precision of the circuit failure is a problem to be solved in the power grid industry.
Disclosure of Invention
In order to improve the detection precision of circuit faults and realize the on-line monitoring of the circuit faults, the invention provides a circuit fault detection method, a system, a device and a medium based on the Internet of things.
In a first aspect, the present invention provides a circuit fault detection method based on the internet of things, which adopts the following technical scheme:
a circuit fault detection method based on the Internet of things comprises the following steps:
monitoring: monitoring N nodes L on the power transmission line;
information acquisition: obtaining the monitoring current of the K-time node L；
Uploading information: monitoring current acquired in the information acquisition stepUploading the information to a storage database;
establishing a storage database: monitoring current uploaded in stored information uploading stepInformation of (2);
current component calculation: the method includes a periodic component calculation step and a non-periodic component calculation step:
calculating a periodic component: calculating the monitored currentPeriodic component +.>Periodic component->The calculation model of (2) is as follows:
；
calculating non-periodic components: calculating the monitored currentNon-periodic component>Non-periodic component->The calculation model of (2) is as follows:
；
in the method, in the process of the invention,is the initial phase;
actual phase calculation: calculating the actual phaseActual phase->The calculation model of (2) is as follows:
；
calculating a phase difference value: calculating a phase difference valueThe method comprises the steps of carrying out a first treatment on the surface of the Phase difference value->The calculation model of (2) is as follows:
；
in the method, in the process of the invention,fto monitor the currentM is a constant; />Phase of monitor current for nth node, +.>Phase of monitor current for N-M th node,/->The phase of the monitor current for the N-M-1 node;
phase fluctuation judgment: setting a first threshold valueA second threshold +.>If->∈[/>]The current in the power transmission line is stable, and the power transmission line does not have faults; if->∉[/>]The current in the transmission line is unstable and the transmission line fails.
By adopting the technical scheme, when the power transmission line is subjected to fault detection, N nodes on the power transmission line are subjected to current monitoring, each node is subjected to K times of monitoring, and then the monitoring current is obtainedAfter that, for the monitoring current->Periodic component +.>Non-periodic component +.>Calculation is performed by periodic component ∈ ->Non-periodic component +.>Obtaining a monitoring current->Is +.>Difference in phase->If->∈[/>]The current in the power transmission line is stable, and the power transmission line does not have faults; if->∉[/>]The current in the power transmission line is unstable, the power transmission line is in fault, and K monitoring points are used for monitoring the power transmission line at moment when the power transmission line is subjected to fault detection, so that information about whether the power transmission line is in fault or not can be rapidly obtained, whether the current is stable or not is judged according to the fluctuation condition of a phase difference value due to the fluctuation of the current caused by the fluctuation of the phase, and the precision of the power transmission line fault detection is improved.
Optionally, the phase fluctuation judging step is further provided with a fault position determining step and an output step;
fault location determination: in the phase fluctuation judging step∉[/>]When the fault is detected, the N-M nodes are determined to be fault positions, and an output step is executed;
and (3) outputting: the output fault location is the nth-M node.
By adopting the technical scheme, when the phase fluctuation judging step∉[/>]When the phase fluctuation of the current does not fall within the normal range, the fluctuation larger phase difference value +.>And further, a monitoring point with a fault is obtained, and further, accurate positioning is carried out on the phase of the power transmission line with the fault.
Optionally, an extremum calculating step and an extremum judging step are further arranged after the phase fluctuation judging step;
extremum meterAnd (3) calculating: calculating the current extremum I of a node m Current extremum I of node m The calculation model of (2) is as follows:
；
judging extremum: setting a stable current value I Q If I m ＞I Q Or I m ＜I Q If there is a fault in the transmission line, if I m ＝I Q No fault occurs in the transmission line.
By adopting the technical scheme, because the power transmission line breaks or short circuit on the power transmission line can cause the extremum change of the current when the power transmission line breaks down, when the detected current extremum is not equal to the stable power transmission current on the power transmission line, the power transmission line is proved to break down, and the power transmission line is judged whether to break down or not by calculating the current extremum and comparing the current extremum with the stable current value, so that the on-line detection of whether the power transmission line breaks down or not is realized.
In a second aspect, the present invention provides a circuit fault detection system based on the internet of things, which adopts the following technical scheme:
the circuit fault detection system based on the Internet of things comprises a monitoring terminal and a detection terminal, wherein the monitoring terminal comprises a current sensor, an acquisition module, an uploading module and a storage module, and the detection terminal comprises a calculation module I, a calculation module II, a calculation module III, a calculation module IV, a calculation module V and a judgment module I; the current sensors are arranged on the power transmission line, and K current sensors are arranged;
a current sensor: the output end is in electrical signal connection with the input end of the acquisition module and is used for monitoring N nodes L on the power transmission line;
the acquisition module is used for: the input end is electrically connected with the output end of the current sensor, the output end is electrically connected with the input end of the uploading module, and the monitoring current of the K nodes L is obtained；
And an uploading module: the input end is electrically connected with the output end of the acquisition module, the output end is electrically connected with the input end of the storage module and is used for acquiring the monitoring current in the acquisition moduleUploading information to a storage module;
and a storage module: the output end is in electrical signal connection with the input end of the computing module I and is used for storing the information uploaded by the uploading module;
calculation module I: the output end is connected with the input end of the computing module II in an electric signal manner, and the monitoring current is calculatedPeriodic component +.>Periodic component->The calculation model of (2) is as follows:
the method comprises the steps of carrying out a first treatment on the surface of the In (1) the->Is the initial phase;
calculation module II: the output end is electrically connected with the input end of the calculation module III to calculate the monitoring currentNon-periodic component>Non-periodic component->The calculation model of (2) is as follows:
；
calculating a module III: the output end is electrically connected with the input end of the calculation module IV to calculate the actual phaseActual phase->The calculation model of (2) is as follows:
；
calculation module IV: the output end is electrically connected with the input end of the calculation module V and is used for calculating the actual phaseActual phase->The calculation model of (2) is as follows:
；
calculation module V: the output end and the judging module I calculate the phase difference valueThe method comprises the steps of carrying out a first treatment on the surface of the Phase difference value->The calculation model of (2) is as follows:
；
in the method, in the process of the invention,fto monitor the currentM is a constant; />Phase of monitor current for nth node, +.>Phase of monitor current for N-M th node,/->The phase of the monitor current for the N-M-1 node;
judging module I: setting a first threshold in the judging module IA second threshold +.>If->∈[/>]The current in the power transmission line is stable, and the power transmission line does not have faults; if->∉[/>]The current in the transmission line is unstable and the transmission line fails.
Optionally, the detection terminal further comprises a positioning module and an output module;
and a positioning module: the input end is electrically connected with the output end of the judging module I, the output end is electrically connected with the input end of the output module, and when the judging module I is in∉[/>]When the fault is detected, the N-M monitoring points are determined to be fault positions, and an output module is executed;
and an output module: the output fault location is the nth-M node.
Optionally, the detection terminal further comprises a calculation module V and a judgment module II;
calculation module VI: the input end is electrically connected with the output end of the judging module I, the output end is electrically connected with the input end of the judging module II, and the output end is used for calculating the current extreme value I of the node m Current extremum I of node m The calculation model of (2) is as follows:
；
judging module II: the input end is electrically connected with the output end of the computing module VI, and a stable current value I is set Q If I m ＞I Q Or I m ＜I Q If there is a fault in the transmission line, if I m ＝I Q No fault occurs in the transmission line.
In a third aspect, the present invention provides a circuit fault detection device based on the internet of things, which adopts the following technical scheme:
an apparatus comprising a processor and a memory for storing a computer program, the processor for executing the computer program stored by the memory to cause the apparatus to perform the method of the first aspect.
In a fourth aspect, the present invention provides a circuit fault detection medium based on the internet of things, which adopts the following technical scheme:
a medium having a computer program stored thereon; the computer program, when executed by a processor, implements the method as described in the first aspect.
In summary, the present invention includes at least one of the following beneficial technical effects:
1. because K monitoring points are monitored at the moment when the power transmission line is subjected to fault detection, the information of whether the power transmission line is faulty or not can be obtained rapidly, and whether the current is stable or not is judged through the fluctuation condition of the phase difference value due to the fluctuation of the current caused by the fluctuation of the phase, so that the precision of the fault detection of the power transmission line is improved.
2. When the phase fluctuation of the current is not in the normal range, the phase difference value with larger fluctuation is calculatedAnd further, a monitoring point with a fault is obtained, and further, accurate positioning is carried out on the phase of the power transmission line with the fault.
3. When the power transmission line breaks down, the extremum of the current can be changed due to open circuit or short circuit on the power transmission line, when the detected extremum of the current is not equal to the stable power transmission current on the power transmission line, the power transmission line is proved to break down, and the power transmission line is judged whether to break down or not by calculating the extremum of the current and comparing the extremum with the stable current value, so that the on-line detection of whether the power transmission line breaks down or not is realized.
Drawings
FIG. 1 is a schematic flow chart of example 1 of the present application;
FIG. 2 is a system diagram of example 2 of the present application;
fig. 3 is a schematic diagram of a bus communication structure of embodiment 3 of the present application.
Detailed Description
The invention is described in further detail below in connection with fig. 1 to 3.
Example 1: the embodiment discloses a circuit fault detection method based on the internet of things, referring to fig. 1, the circuit fault detection method based on the internet of things comprises the following steps:
s1: monitoring: n nodes L on the transmission line are monitored.
For example: current monitoring is performed on 10 nodes on the power transmission line through a current sensor.
S2: information acquisition: obtaining the monitoring current of the K-time node L。
For example: the monitoring current obtained by 3 times of monitoring on the 1 st node isThe method comprises the steps of carrying out a first treatment on the surface of the The monitoring current obtained by monitoring the 4 th node is +.>。
S3: uploading information: monitoring current acquired in the information acquisition stepAnd uploading the information to a storage database.
S4: establishing a storage database: monitoring current uploaded in stored information uploading stepIs a piece of information of (a).
S5: current component calculation: the method includes an S51 periodic component calculation step and an S52 non-periodic component calculation step:
s51: calculating a periodic component: calculating the monitored currentPeriodic component +.>Periodic component->The calculation model of (2) is as follows:
。
s52: calculating non-periodic components: calculating the monitored currentNon-periodic component>Non-periodic component->The calculation model of (2) is as follows:
wherein->Is the initial phase.
S6: actual phase calculation: calculating the actual phaseActual phase->The calculation model of (2) is as follows:
。
s7: calculating a phase difference value: calculating a phase difference valueThe method comprises the steps of carrying out a first treatment on the surface of the Phase difference value->The calculation model of (2) is as follows:
；
in the method, in the process of the invention,fto monitor the currentM is a constant; />Phase of monitor current for nth node, +.>Phase of monitor current for N-M th node,/->The phase of the monitor current for the N-M-1 node.
When the power transmission line fails, the current is in a stable state, the phase difference value among the nodes is kept constant, and when the power transmission line fails, the current is unstable, and the phase difference among the nodes can be changed; for example: the phase of the first node is pi, the phase of the second node is pi, and the phase of the third node is three-thirds pi, so that the line fails.
S8: phase fluctuation judgment: setting a first threshold valueA second threshold +.>If->∈[/>]The current in the power transmission line is stable, the power transmission line has no fault temporarily, and the step S10 is executed; if->∉[/>]And (3) if the current in the power transmission line is unstable, the power transmission line fails, and executing the step S9.
S9: fault location determination: in the phase fluctuation judging step∉[/>]And if so, determining the N-M node as a fault position and executing an output step.
S10: and (3) extremum calculation: calculating the current extremum I of a node m Current extremum I of node m The calculation model of (2) is as follows:
；
s11: judging extremum: setting a stable current value I Q If I m ＞I Q Or I m ＜I Q Then inputIf there is a fault in the electrical line, if I m ＝I Q No fault occurs in the transmission line.
S12: and (3) outputting: the output fault location is the nth-M node.
The implementation principle of the circuit fault detection method based on the Internet of things of the embodiment is as follows:
the current is monitored on the transmission line through setting a current sensor, the monitoring current of the node is obtained, the obtained monitoring current is uploaded to a storage database, then monitoring current data in the storage database is called, and the periodic component of the monitoring current is calculatedNon-periodic component +.>By periodic component->Non-periodic component +.>Calculating the actual phase of the monitored current, +.>By the actual phase->Calculating the N node and the +.>Personal node, th>For the phase difference between the N-M-1 th nodes +.>Then set the first threshold +.>A second threshold +.>For phase difference->To judge the fluctuation of (1) if->∈[/>]The current in the transmission line is stable, no fault occurs in the transmission line, and the current extremum I of the node is calculated m And to the current extremum I of the node m Judging and setting a stable current value I Q If I m ＞I Q Or I m ＜I Q If there is a fault in the transmission line, if I m ＝I Q The transmission line has no fault; if->∉[/>]And if the current in the power transmission line is unstable, the power transmission line fails, the fault position is determined to be the N-M node, and the fault position is output.
Example 2: the embodiment discloses a circuit fault detection system based on the internet of things, referring to fig. 2, the circuit fault detection system based on the internet of things comprises a monitoring terminal and a detection terminal, wherein the monitoring terminal comprises a current sensor, an acquisition module, an uploading module and a storage module, and the detection terminal comprises a calculation module I, a calculation module II, a calculation module III, a calculation module IV, a judgment module I, a positioning module, a calculation module V, a calculation module VI, a judgment module II and an output module; the current sensors are arranged on the power transmission line, and K current sensors are arranged;
a current sensor: the output end is connected with the input end electric signal of the acquisition module and is used for monitoring N nodes L on the power transmission line.
The acquisition module is used for: the input end is electrically connected with the output end of the current sensor, the output end is electrically connected with the input end of the uploading module, and the monitoring current of the K nodes L is obtained。
And an uploading module: the input end is electrically connected with the output end of the acquisition module, the output end is electrically connected with the input end of the storage module and is used for acquiring the monitoring current in the acquisition moduleAnd uploading the information to a storage module.
And a storage module: the output end is electrically connected with the input end of the computing module I and is used for storing the information uploaded by the uploading module.
Calculation module I: the output end is connected with the input end of the computing module II in an electric signal manner, and the monitoring current is calculatedPeriodic component +.>Periodic component->The calculation model of (2) is as follows:
the method comprises the steps of carrying out a first treatment on the surface of the In (1) the->Is the initial phase.
Calculation module II: the output end is electrically connected with the input end of the calculation module III to calculate the monitoring currentNon-periodic component>Non-periodic component->The calculation model of (2) is as follows:
。
calculating a module III: the output end is electrically connected with the input end of the calculation module IV to calculate the actual phaseActual phase->The calculation model of (2) is as follows:
。
calculation module IV: the output end is electrically connected with the input end of the calculation module V and is used for calculating the actual phaseActual phase->The calculation model of (2) is as follows:
。
calculation module V: the output end is electrically connected with the input end of the judging module I and is used for calculating the phase difference valueThe method comprises the steps of carrying out a first treatment on the surface of the Phase difference value->The calculation model of (2) is as follows:
；
in the method, in the process of the invention,fto monitor the currentM is a constant; />Phase of monitor current for nth node, +.>Phase of monitor current for N-M th node,/->The phase of the monitor current for the N-M-1 node.
Judging module I: setting a first threshold in the judging module IA second threshold +.>If->∈[/>]The current in the power transmission line is stable, and the power transmission line does not have faults; if->∉[/>]The current in the transmission line is unstable and the transmission line fails.
And a positioning module: the input end is electrically connected with the output end of the judging module I, the output end is electrically connected with the input end of the output module, and when the judging module I is in∉[/>]And when the fault is detected, the N-M monitoring points are determined to be fault positions, and the output module is executed.
Calculation module VI: the input end is electrically connected with the output end of the judging module I, the output end is electrically connected with the input end of the judging module II, and the output end is used for calculating the current extreme value I of the node m Current extremum I of node m The calculation model of (2) is as follows:
；
judging module II: the input end is electrically connected with the output end of the computing module VI, and a stable current value I is set Q If I m ＞I Q Or I m ＜I Q If there is a fault in the transmission line, if I m ＝I Q No fault occurs in the transmission line.
And an output module: the output fault location is the nth-M node.
The implementation principle of the circuit fault detection system based on the internet of things of the embodiment is as follows:
the current sensor monitors N nodes L on the power transmission line, and the acquisition module acquires the monitoring current of K nodes LThe uploading module is used for obtaining the monitoring current +.>And uploading the information to a storage module, and storing the information uploaded by the uploading module by the storage module.
The calculation module I calculates the monitoring currentPeriodic component +.>The calculation module II calculates the monitoring current +.>Non-periodic component>The calculation module III calculates the actual phase +.>The calculation module IV calculates the actual phase +.>The calculation module V calculates the phase difference value +.>The method comprises the steps of carrying out a first treatment on the surface of the Setting a first threshold value +.>A second threshold +.>If->∈[/>]The current in the power transmission line is stable, and the power transmission line does not have faults; if->∉[/>]The current in the transmission line is unstable and the transmission line fails. When the transmission line fails, the module I is judged to be +.>∉[/>]And when the fault is detected, the N-M monitoring points are determined to be fault positions, and the output module is executed. Calculation module VI calculates the current extremum I of the node m The judgment module II sets a stable current value I Q If I m ＞I Q Or (b)I m ＜I Q If there is a fault in the transmission line, if I m ＝I Q No fault occurs in the transmission line.
Example 3: the embodiment discloses a circuit fault detection device based on thing networking, referring to fig. 3, detection device includes:
a memory for storing a computer program;
a processor for executing the computer program stored in the memory, and further implementing the method described in embodiment 1.
The storage may include mass storage for storing data or instructions. By way of example, and not limitation, the storage may comprise a hard disk, floppy disk, flash memory, optical disk, magneto-optical disk, magnetic tape, or a combination of two or more of the foregoing. Where appropriate, the reservoir may comprise removable or non-removable (or fixed) media. The storage may be internal or external to the data processing apparatus, where appropriate. In a particular embodiment, the storage is a non-volatile solid state storage. In particular embodiments, the storage includes Read Only Memory (ROM). The ROM may be mask-programmed ROM, programmable ROM (PROM), erasable PROM (EPROM), electrically Erasable PROM (EEPROM), electrically rewritable ROM (EBROM), or a combination of two or more of the above, where appropriate.
Example 4: the present embodiment discloses a computer storage medium for circuit fault detection based on the internet of things, wherein the computer storage medium stores a program, and when the program is executed, the program can implement part or all of the steps of the method described in embodiment 1.
The above embodiments are not intended to limit the scope of the present invention, so: all equivalent changes in structure, shape and principle of the invention should be covered in the scope of protection of the invention.

Claims (8)

1. A circuit fault detection method based on the Internet of things is characterized by comprising the following steps of: the method comprises the following steps:
monitoring: monitoring N nodes L on the power transmission line;
information acquisition: obtaining the monitoring current of the K-time node L；
Uploading information: monitoring current acquired in the information acquisition stepUploading the information to a storage database;
establishing a storage database: monitoring current uploaded in stored information uploading stepInformation of (2);
current component calculation: the method includes a periodic component calculation step and a non-periodic component calculation step:
calculating a periodic component: calculating the monitored currentPeriodic component +.>Periodic component->The calculation model of (2) is as follows:
；
calculating non-periodic components: calculating the monitored currentNon-periodic component>Non-periodic component->The calculation model of (2) is as follows:
；
in the method, in the process of the invention,is the initial phase;
actual phase calculation: calculating the actual phaseActual phase->The calculation model of (2) is as follows:
；
calculating a phase difference value: calculating a phase difference valueThe method comprises the steps of carrying out a first treatment on the surface of the Phase difference value->The calculation model of (2) is as follows:
；
in the method, in the process of the invention,fto monitor the currentM is a constant; />Phase of monitor current for nth node, +.>For the N-M th sectionThe phase of the monitored current of the point, +.>The phase of the monitor current for the N-M-1 node;
phase fluctuation judgment: setting a first threshold valueA second threshold +.>If->∈[/>]The current in the power transmission line is stable, and the power transmission line does not have faults; if->∉[/>]The current in the transmission line is unstable and the transmission line fails.
2. The circuit fault detection method based on the internet of things according to claim 1, wherein the circuit fault detection method based on the internet of things is characterized in that: the phase fluctuation judging step is further provided with a fault position determining step and an output step;
fault location determination: in the phase fluctuation judging step∉[/>]When the fault is detected, the N-M nodes are determined to be fault positions, and an output step is executed;
and (3) outputting: the output fault location is the nth-M node.
3. The circuit fault detection method based on the internet of things according to claim 2, wherein the circuit fault detection method based on the internet of things is characterized in that: the phase fluctuation judging step is further provided with an extremum calculating step and an extremum judging step;
and (3) extremum calculation: calculating the current extremum I of a node m Current extremum I of node m The calculation model of (2) is as follows:
；
judging extremum: setting a stable current value I Q If I m ＞I Q Or I m ＜I Q If there is a fault in the transmission line, if I m ＝I Q No fault occurs in the transmission line.
4. A circuit fault detection system based on the internet of things, which uses the circuit fault detection method based on the internet of things according to any one of claims 1-3, and is characterized in that: the monitoring terminal comprises a current sensor, an acquisition module, an uploading module and a storage module, and the detection terminal comprises a calculation module I, a calculation module II, a calculation module III, a calculation module IV, a calculation module V and a judgment module I; the current sensors are arranged on the power transmission line, and K current sensors are arranged;
a current sensor: the output end is in electrical signal connection with the input end of the acquisition module and is used for monitoring N nodes L on the power transmission line;
the acquisition module is used for: the input end is electrically connected with the output end of the current sensor, the output end is electrically connected with the input end of the uploading module, and the monitoring current of the K nodes L is obtained；
And an uploading module: the input end is electrically connected with the output end of the acquisition module, and the output end is connected withThe input end of the storage module is electrically connected with the monitoring current acquired by the acquisition moduleUploading information to a storage module;
and a storage module: the output end is in electrical signal connection with the input end of the computing module I and is used for storing the information uploaded by the uploading module;
calculation module I: the output end is connected with the input end of the computing module II in an electric signal manner, and the monitoring current is calculatedPeriodic component +.>Periodic component->The calculation model of (2) is as follows:
the method comprises the steps of carrying out a first treatment on the surface of the In (1) the->Is the initial phase;
calculation module II: the output end is electrically connected with the input end of the calculation module III to calculate the monitoring currentNon-periodic component>Non-periodic component->The calculation model of (2) is as follows:
；
calculating a module III: the output end is electrically connected with the input end of the calculation module IV to calculate the actual phaseActual phase->The calculation model of (2) is as follows:
；
calculation module IV: the output end is electrically connected with the input end of the calculation module V and is used for calculating the actual phaseActual phaseThe calculation model of (2) is as follows:
；
calculation module V: the output end and the judging module I calculate the phase difference valueThe method comprises the steps of carrying out a first treatment on the surface of the Phase difference value->The calculation model of (2) is as follows:
；
in the method, in the process of the invention,fto monitor the currentM is a constant；/>Phase of monitor current for nth node, +.>Phase of monitor current for N-M th node,/->The phase of the monitor current for the N-M-1 node;
judging module I: setting a first threshold in the judging module IA second threshold +.>If->∈[/>]The current in the power transmission line is stable, and the power transmission line does not have faults; if->∉[/>]The current in the transmission line is unstable and the transmission line fails.
5. The circuit fault detection system based on the internet of things according to claim 4, wherein: the detection terminal also comprises a positioning module and an output module;
and a positioning module: the input end is electrically connected with the output end of the judging module I, the output end is electrically connected with the input end of the output module, and when the judging module I is in∉[/>]When the fault is detected, the N-M monitoring points are determined to be fault positions, and an output module is executed;
and an output module: the output fault location is the nth-M node.
6. The circuit fault detection system based on the internet of things according to claim 5, wherein: the detection terminal also comprises a calculation module V and a judgment module II;
calculation module VI: the input end is electrically connected with the output end of the judging module I, the output end is electrically connected with the input end of the judging module II, and the output end is used for calculating the current extreme value I of the node m Current extremum I of node m The calculation model of (2) is as follows:
；
judging module II: the input end is electrically connected with the output end of the computing module VI, and a stable current value I is set Q If I m ＞I Q Or I m ＜I Q If there is a fault in the transmission line, if I m ＝I Q No fault occurs in the transmission line.
7. A circuit fault detection device based on thing networking, its characterized in that: comprising a processor and a memory for storing a computer program, the processor being configured to execute the computer program stored by the memory to cause the apparatus to perform the method of any one of claims 1-3.
8. The utility model provides a circuit fault detection medium based on thing networking which characterized in that: a computer program stored thereon; the method is characterized in that: the computer program implementing the method according to any of claims 1-3 when executed by a processor.
CN202410032014.5A 2024-01-10 2024-01-10 Circuit fault detection method, system, device and medium based on Internet of things Withdrawn CN117538689A (en)

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Citations (6)

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Publication number Priority date Publication date Assignee Title
KR100709980B1 (en) * 2005-10-21 2007-04-20 명지대학교 산학협력단 Method and apparatus for detecting a fault section using comparison of phase difference and magnitude difference bewteen zero phase currents in ungrounded distribution power systems
CN104049179A (en) * 2014-07-03 2014-09-17 武汉三相电力科技有限公司 Line fault optimized positioning method based on measurement on distributed traveling waves
CN108919054A (en) * 2018-07-05 2018-11-30 国网上海市电力公司 The intelligent power distribution network short circuit fault localization method estimated based on load and branch line
CN115932461A (en) * 2022-05-31 2023-04-07 上海交通大学 Power transmission line fault positioning method
CN116520072A (en) * 2023-02-10 2023-08-01 广州长川科技有限公司 Cable fault positioning method and equipment
WO2023216553A1 (en) * 2022-05-11 2023-11-16 广东电网有限责任公司东莞供电局 Multi-fault diagnosis method for power distribution network, and system

Patent Citations (6)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
KR100709980B1 (en) * 2005-10-21 2007-04-20 명지대학교 산학협력단 Method and apparatus for detecting a fault section using comparison of phase difference and magnitude difference bewteen zero phase currents in ungrounded distribution power systems
CN104049179A (en) * 2014-07-03 2014-09-17 武汉三相电力科技有限公司 Line fault optimized positioning method based on measurement on distributed traveling waves
CN108919054A (en) * 2018-07-05 2018-11-30 国网上海市电力公司 The intelligent power distribution network short circuit fault localization method estimated based on load and branch line
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